1 to 25 of 52 Remote/Hybrid MLOps Jobs

validation techniques to improve training pipelines Ensure data privacy and governance standards suitable for financial services Engineering best practices Contribute to DevOps and MLOps pipelines Implement robust version control, testing and CI/CD workflows Support reliable deployment and monitoring of models in production environments Technical leadership Mentor engineers ...

every model we build is fair, free from bias, and explainable to consumers, customers, and regulators. Engineering & Deployment: Work within the engineering team on MLOps to containerise, deploy, and monitor models in high-scale production. Skills & Requirements Core Data Science: Foundational Stats: You must have an excellent grasp of Linear ...

programming skills Hands-on experience with PyTorch Experience with Hugging Face transformers or similar frameworks Solid experience deploying ML solutions on AWS Understanding of MLOps, model deployment and performance optimisation Ability to work in a consultancy environment with multiple clients Desirable: Experience with LLMs, RAG pipelines or generative AI applications ...

multimodal AI systems. Familiarity with AI orchestration tools (e.g., LangChain, LlamaIndex, Ray, Dask). Strong programming skills in Python, Go, or JavaScript. Understanding of MLOps and CI/CD pipelines for AI/ML models. Knowledge of security best practices for AI applications. Strong analytical and problem-solving abilities. Excellent ...

services. Apply data modelling concepts (e.g., medallion architecture) and ensure data quality and governance. Collaborate with DevOps teams to automate CI/CD and MLOps processes using Azure DevOps, Kubernetes, and Terraform. Visualize and communicate insights using Power BI, Tableau, and PowerApps. Mentor junior engineers and contribute to internal knowledge ...

self-start when necessary. • Flexibility, we pride ourselves on doing what is necessary to make the whole organisation successful. Bonus Points: • Knowledge of MLOps principles and best practices. • Experience with distributed computing and large-scale data processing. How to apply? Please send a CV to danni@cortechtalentsolutions.co.uk ...

knowledge — spectral features, neural codecs, generative audio models Experience deploying models to cloud inference (AWS or GCP) with awareness of latency and cost tradeoffs MLOps competency — experiment tracking, model versioning, evaluation pipelines, ML CI Experience with Python and modern ML frameworks (PyTorch, JAX) Excellent verbal and written English communication skills ...

. AI & NLP - Practical experience in Artificial Intelligence and Natural Language Processing (NLP) . Cloud Platforms - Hands-on experience with AWS or Azure environments. MLOps & Deployment Experience in: - Model deployment and productionization - Model governance and lifecycle management - Version control tools such as Git - CI/CD pipelines for ML workflows ...

Skills and Qualifications Experience working with cloud platforms such as Azure, AWS, or Google Cloud. Background in deploying machine learning models into production environments (MLOps experience is advantageous). Hands-on experience with big-data or distributed computing tools such as Spark and Databricks. Familiarity with visualisation tools such ...

Supporting the full ML lifecycle, from experimentation to deployment and optimisation. Applying best practices in data engineering and contributing to architectural decisions. Using modern MLOps tools and CI/CD approaches to improve reliability and efficiency. Contributing to a culture of knowledge-sharing and continuous improvement. Technical Experience Were looking ...

solid understanding of machine learning fundamentals and data workflows 💬 Strong communication skills and a collaborative mindset ⭐ Big bonus points for: ⚙️ Exposure to ML pipelines, MLOps, or production ML systems 📦 Experience with tools such as Databricks, Snowflake, or similar platforms 🔍 Familiarity with version control, testing practices, or CI/CD workflows ...

Databricks, LangChain , vector databases , or LLM orchestration tools . Knowledge of RAG pipelines , transformers , and modern AI architectures . Understanding of deployment or MLOps best practices (Azure experience a plus). Recent, hands-on experience with applied LLM projects . Strong communication and stakeholder engagement skills. A Master’s degree ...

R. Experience with machine learning frameworks and libraries (e.g. TensorFlow, PyTorch, Scikit-learn). Familiarity with cloud platforms (AWS, Azure or Google Cloud) and MLOps practices. Knowledge of automation technologies including RPA platforms (e.g. UiPath) and orchestration tools (Airflow, Kubeflow). Soft Skills: Excellent problem-solving and analytical capabilities. Strong ...

internal stakeholders Excellent coding practice using Python and associated ML packages (HuggingFace, TensorFlow, PyTorch), following best practices Experience developing robust ML pipelines with MLOps tools for model training, monitoring and deployment Experience of appropriate version control and environment management (such as venvs or Docker) Experience of writing technical project proposals ...

data workflows 💬 Strong communication skills and a collaborative mindset ⭐ Big bonus points for: ❄️ Experience with Snowflake 🧱 Experience with Databricks ⚙️ Exposure to ML pipelines, MLOps, or production ML systems If you’re excited about building AI systems, learning fast, and growing your career in a supportive, high-impact environment ...

GCP. A track record of building or scaling an AI/Automation strategy. Desirable extras include: Hands-on coding experience. Familiarity with MLOps or RPA tooling. Experience with advanced analytics, data engineering or architecture. Knowledge of industry compliance standards (ISO, Cyber Essentials). Experience with RPA platforms such as Robert ...

Searches: ML Engineer/AI Engineer/Cloud Engineer/Machine Learning/Cloud AI/Google Cloud/GCP/Vertex AI/MLOps/ML Ops/AIOPs/AI Ops/ ...

automation Containerisation and orchestration Monitoring and observability tools Experience in the defence or advanced technology sector Experience with GPU based computer environments Experience with MLOps and associated tooling Experience with data pipelines Experience with Infrastructure as Code Experience with security integration in DevOps i.e. DevSecOps Service-oriented with effective communication ...

automation Containerisation and orchestration Monitoring and observability tools Experience in the defence or advanced technology sector Experience with GPU based computer environments Experience with MLOps and associated tooling Experience with data pipelines Experience with Infrastructure as Code Experience with security integration in DevOps i.e. DevSecOps Service-oriented with effective communication ...

issues and implement effective resolutions. Optimize application performance using Azure monitoring tools (Azure Monitor, App Insights). Improve SQL query performance for applications and MLOps workflows. Perform proactive monitoring, troubleshooting, and enhancement of application functionality. Integration & Documentation Integrate third-party APIs/services ensuring seamless communication. Document technical decisions, architectural ...

concept to production Establish AI operating models, best practices, and responsible AI frameworks Build and lead high-performing multidisciplinary teams (Data Science, ML Engineering, MLOps) Identify use cases across functions (customer experience, operations, knowledge management, automation) Ensure scalability, security, and compliance of AI platforms Required Experience Proven leadership delivering Generative … deep learning, model optimisation Evaluation frameworks and guardrails Data & Platforms Vector databases (Pinecone, Weaviate, FAISS, Milvus) Knowledge graphs and semantic search Data engineering pipelines MLOps & Deployment CI/CD for ML, model monitoring, versioning Kubernetes, Docker, serverless architectures MLflow, Kubeflow, SageMaker or similar Cloud & Architecture Azure AI, AWS AI/ ...

maintain robust CI/CD pipelines (GitHub Actions, CircleCI, Jenkins) to automate testing, builds, and deployments across dev/staging/production environments. • Implement MLOps workflows to streamline model deployment, versioning, and monitoring for our AI/ML products. • Automate infrastructure provisioning (Terraform), configuration management, and deployment processes using scripting … orchestration (Docker, Kubernetes, ECS, Fargate) • Proven track record building and maintaining CI/CD pipelines (GitHub Actions, CircleCI, Jenkins, GitLab CI) • Experience with MLOps and supporting ML model deployment workflows (AWS Sagemaker, Lambda, containerized deployments) • Proficiency in scripting and automation (Python, Bash, Go) • Strong experience with monitoring and observability tools ...

Role/Job Title: AI & ML Senior Engineer Work Location: London The JJ Mack Building, 33 Charterhouse St, EC1M 6HA Mode of Working: Hybrid If Hybrid, how many days are required in office?: Minimum 2 ...

coaches, analysts, and execs Highly Desirable Skills Football Analytics Experience : Familiarity with football-specific datasets (event, tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming ...

applied Machine Learning and modern AI engineering concepts Support learners across areas such as Python-based ML development, LLMs, NLP, Generative AI, and modern MLOps approaches (you don’t need be an expert in every area) Help learners understand how models move from experimentation into real-world use Translate complex ...